Failed to use transforms.ToTensor and transforms.Normalize to normalize the MNIST dataset

Question

I used the following code to normalize the MNIST dataset, when I print the first sample, it fails to normalize as the max element is 255, not 1.

train_transform = transforms.Compose([
   transforms.ToTensor(), 
   transforms.Normalize((0.1307,), (0.3081,))])

train_set = torchvision.datasets.MNIST(
   root=data_dir, train=True, download=True, transform=train_transform)

When I check the range of the dataset input images:

print("min:%f max:%f" %(train_set.data.min(), train_set.data.max()))
output result:min:0.000000 max:255.000000

I was expecting [0, 1] instead, I don't know why that is. Is there something wrong?

Answer 1

You can use those options then

const element = await page.$$("text='element'");
if (element) {
    // ...
}

or

const element = await page.$$("text='element'");
if (element.length) {
    // ...
}

or

await expect(page.locator(".MyClass")).toHaveCount(0)

Answer 2

You have several options depending on particular needs; If your element is not hidden you can use:

page.locator("your_locator").isVisible();

If it is hidden you can try with.

try{
page.waitForSelector("your_locator",{timeout:5000});}
catch(){
//element is not found do next
}